Quotes

A study cited in the paper notes publisher websites utilize an average of 13.5 (and up to 70 in some cases) third parties. A visit to one popular U.S. tabloid triggered a user interaction with some 352 other web servers, according to a 2014 U.S. Senate subcommittee study of the issue.

Many of those interactions were benign; however, some of those third parties may have been using cookies or other technology to compile data on consumers without their explicit consent, according to the study. Data mined by the practice can include users’ interests, browsing history, location, and past-purchase history.

Even anonymous data can be de-anonymized with enough data points. The web is broken, in that we think it’s doing one thing (letting people publish content) when it’s actually doing something else (surveilling everyone who comes within 100′ of a website, and using that data with no oversight or visibility).

For a real eye-opener, try running the Lightbeam Firefox add-on. It builds a visualization of the collusion between websites and data-miners.

Update: Nick Heer pointed out that the Globe and Mail article about privacy-invading trackers had an impressive 18 trackers itself, as reported by Ghostery. Awesome. (It’s showing 9 trackers for me now)

…blogging either needs its own mechanisms of ambient humanity — which it’s had, in the form of links, trackbacks, conversations, even (gulp) comments, all of which replicated at least a fraction of the buzz that social media has — or it needs a kind of escape velocity to break that gravitational pull. Gravity or speed. Or a hybrid of both.

We’ve seen another way. It’s possible, and we know that because it worked for years, at internet scale. But the mechanisms of ambient humanity in the Big Silos won because most people really don’t care about the infrastructure. People just want to feel connected to people, and there was less friction in the silos – at the cost of giving up and/or losing control.

There are absolutely parallels in edtech. Instructors and students largely interact with each other online via the institutional learning management system, rather than richer distributed venues designed for each individual context. Or, rather, some courses use those interesting non-sanctioned venues anyway, because they suit their needs, but without the blessing of the institution and at risk – both personal and institutional.

Student data (names, emails, ID numbers, grades, etc) needs to be tightly managed by the institution for very good reasons – we can’t violate the privacy of our students, either through active leaks or from passive breaches due to data becoming siphoned off into other tools without our control. I get that we need to control the data. But we’re also setting up a mirror of the social-media-to-corporate-silo model, which has been shown to be harmful in so many ways.

So. How to support the decentralized needs of an incredibly diverse and interesting ecosystem of communities, while protecting sensitive personal information, without stifling the interesting and creative activities that are possible when students and instructors have more control over their own environments?

Yet our taste for convenience begets more convenience, through a combination of the economics of scale and the power of habit. The easier it is to use Amazon, the more powerful Amazon becomes — and thus the easier it becomes to use Amazon. Convenience and monopoly seem to be natural bedfellows.

(Extend that line of thought to Twitter/Facebook vs. individually owned websites distributed across the internet as a heterogeneous and diverse culture of sharing and interacting…)

And

We are spoiled by immediacy and become annoyed by tasks that remain at the old level of effort and time. When you can skip the line and buy concert tickets on your phone, waiting in line to vote in an election is irritating.

This is why blogging largely died out (Alan pointed out in the comments that blogging has definitely not died out, and that there are still bajillions of active blogs. Which is awesome. But it still feels different now, to my curmudgeonish self) , replaced with tweeting. This is why RSS largely died out, (also, not so much actually dying out…) replaced with algorithmic activity streams. Because it’s easier to just numbly follow a stream. This has huge implications on how we interact with each other, and how we formalize our thoughts. It’s a race to the bottom, to the easiest possible form.

That bit resonated. Actually, the whole article resonated a bit more than I’m comfortable with. Small talk becomes a bit like navigating a mental minefield. “How are you?” is either answered with a gentle lie, or with the truth. The gentle lie is what people are usually asking for, and, frankly, is what I usually want to say anyway. The truth is brutal and scary and life-altering and nuanced and exhausting. “I’m fine. How are you?”

Algorithms, tuned not to help readers but to help advertisers. Intermittent reinforcement tuned to maximize engagement/addiction. This is some scary shit, but it’s the web in 2018. We can do better.

But whereas Twitter sort of stumbled upon addictiveness through the weird 140-character limit, Facebook mixed a new, super-potent active ingredient into their feed called Machine Learning. They basically said, “look, we are not going to show everybody every post,” and they used the new Midas-style power of machine learning and set it in the direction of getting people even more hyper-addicted to the feed. The only thing the ML algorithm was told to care about was addiction, or, as they called it, engagement. They had a big ol’ growth team that was trying different experiments and a raw algorithm that was deciding what to show everybody and the only thing it cared about was getting you to come back constantly.

Good news! Except that won’t help. It will only tighten the feedback loop and prop up the bubble. If you’re more likely to see things from your friends, you’re less likely to see things serendipitously. You only see what you agree with. Therefore everyone agrees with you. Bubble intensifies…

Indigenous pedagogy, which refers to a way of teaching using Indigenous educational principles, is grounded in creating, fostering and sustaining good relationships between student and teacher. Teaching moments are found in the human-to-human interactions which are reciprocal — my students understand that I have certain knowledge and experience they can learn from and I understand that I, too, can learn from my students.

and

Rather than compromising excellence, Indigenous epistemology, therefore, offers students the opportunity to strive for their full potential without compromising their human dignity or those of other cultures.

Fantastic. Indigenization is as much about shifting the power structure as it is about learning the history.

The article isn’t as hyperbolic as I was braced for, and connects the recent spate of Facebook billionaires lamenting that they just discovered that Facebook may not be the best thing for people or society (but thanks for the $billions).

I’m not about to say that having supercomputers in our pockets, wirelessly connected to the sum of published human knowledge and to every other pocket-supercomputer, is anything but an incredible boon for humanity. But, the way that capitalism and advertising revenue combined with algorithmic distribution to maximize “engagement” and tie into the feedback loop to boost ad revenue and then tweak algorithms and then boost ad revenue etc. etc. ad nauseum? Yeah. That might need a little work.

To ensure that our eyes remain firmly glued to our screens, our smartphones – and the digital worlds they connect us to – internet giants have become little virtuosos of persuasion, cajoling us into checking them again and again – and for longer than we intend. Average users look at their phones about 150 times a day, according to some estimates, and about twice as often as they think they do, according to a 2015 study by British psychologists.

Add it all up and North American users spend somewhere between three and five hours a day looking at their smartphones. As the New York University marketing professor Adam Alter points out, that means over the course of an average lifetime, most of us will spend about seven years immersed in our portable computers.

Modern computing security is like a flimsy house that needs to be fundamentally rebuilt. In recent years, we have suffered small collapses here and there, and made superficial fixes in response. There has been no real accountability for the companies at fault, even when the failures were a foreseeable result of underinvestment in security or substandard practices rather than an outdated trade-off of performance for security.

Practice grants: This stream of grants supports our pursuit of professional learning about research-informed teaching and learning. Practice grants are one-year grants, individual or collaborative and can receive funding up to $7,500.

Lesson study: These grants support team-based studies of a single lesson, carefully developed and studied to promote a significant learning goal. Lesson study grants are one or two year grants for teams of three to six members. Teams can receive funding up to $7,500 per year, to a maximum of $15,000 per year, for the entire team.

Scholarship of Teaching and Learning: These projects are formal, evidence-based studies to better understand or improve student learning. They can be individual or collaborative and one or two years in duration. Individual projects can receive up to $10,000 per year, to a maximum of $20,000 for two years. Collaborative projects can receive up to $20,000 per year, to a maximum of $40,000 for two years.

The grants have been offered for a few years now, and the program is adapting to incorporate new initiatives. It’s become one of the most transformative things we do as a university to support innovation teaching and learning.

When it comes to security, where will this sea of abandoned devices get security patches from? Who will write them, and how will they get paid?Like Ward, I worry that it’s not just an internet of things, but a proprietary mess of interdependent services built on the shifting sands of unstable business models. Unless we develop standards and protocols that reduce that proprietary interdependency we’re eventually going to have a lot bigger problem on our hands than Twitter outages.